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Efficient Detection of Parkinson Disease Using Multiple Machine Learning Techniques

Muralikrishna, Abishek Bangalore (2020) Efficient Detection of Parkinson Disease Using Multiple Machine Learning Techniques. Masters thesis, Dublin, National College of Ireland.

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Abstract

In the recent years there has been a significant surge in the diagnosis and monitoring of several diseases, out of which Parkinson disease (PD) is one of them which is commonly found in the elderly population. In this project we aim at developing a simplified and efficient screening method to diagnose PD benefiting medical practitioners who can screen the patients remotely. Currently, a series of spiral drawings are used as standard tests, different approaches are proposed that proves to provide better results compared to spiral drawings using the advanced Deep Neural Network models (Resnet 34, Resnet 50, Vgg19)in this project. Vgg19 outperforms Residual network models for spiral, wave and fusion based data. It is also observed that wave drawings are more insightful compared to spiral and fusion based data.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

R Medicine > Healthcare Industry
T Technology > T Technology (General) > Information Technology
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Dan English
Date Deposited: 18 Jan 2021 13:13
Last Modified: 18 Jan 2021 13:13
URI: http://norma.ncirl.ie/id/eprint/4361

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